Reduction of Admit Wait Times: The Effect of a Leadership-based Program

ORIGINAL CONTRIBUTION Reduction of Admit Wait Times: The Effect of a Leadership-based Program Pankaj B. Patel, MD, Mary A. Combs, and David R. Vinson, MD Abstract Objectives: Prolonged admit wait times in the emergency department (ED) for patients who require hospitalization lead to increased boarding time in the ED, a significant cause of ED congestion. This is associated with decreased quality of care, higher morbidity and mortality, decreased patient satisfaction, increased costs for care, ambulance diversion, higher numbers of patients who leave without being seen (LWBS), and delayed care with longer lengths of stay (LOS) for other ED patients. The objective was to assess the effect of a leadership-based program to expedite hospital admissions from the ED. Methods: This before-and-after observational study was undertaken from 2006 through 2011 at one community hospital ED. A team of ED and hospital leaders implemented a program to reduce admit wait times, using a computerized hospital-wide tracking system to monitor inpatient and ED bed status. The team collaboratively and consistently moved ED patients to their inpatient beds within an established goal of 60 minutes after an admission decision was reached. Top leadership actively intervened in real time by contacting staff whenever delays occurred to expedite immediate solutions to achieve the 60-minute goal. The primary outcome measures were the percentage of ED patients who were admitted to inpatient beds within 60 minutes from the time the beds were requested and ED boarding time. LOS, patient satisfaction, LWBS rate, and ambulance diversion hours were also measured. Results: After ED census, hospital admission rates, and ED bed capacity were controlled for using a multivariable linear regression analysis, the admit wait time reduction program contributed to an increase in patients being admitted to the hospital within 60 minutes by 16 percentage points (95% confidence intervals [CI] = 10 to 22 points; p < 0.0001) and a decrease in boarding time per admission of 46 minutes (95% CI = 63 to 82 minutes; p < 0.0001). LOS decreased for admitted patients by 79 minutes (95% CI = 55 to 104 minutes; p < 0.0001), for discharged patients by 17 minutes (95% CI = 12 to 23 minutes; p < 0.0001), and for all patients by 34 minutes (95% CI = 25 to 43 minutes; p < 0.0001). Patient satisfaction increased 4.9 percentage points (95% CI = 3.8 to 6.0 points; p < 0.0001). LWBS patients decreased 0.9 percentage points (95% CI = 0.6 to 1.2 points; p < 0.0001) and monthly ambulance diversion decreased 8.2 hours (95% CI = 4.6 to 11.8 hours; p < 0.0001). Conclusions: A leadership-based program to reduce admit wait times and boarding times was associated with a significant increase in the percentage of patients admitted to the hospital within 60 minutes and a significant decrease in boarding time. Also associated with the program were decreased ED LOS, LWBS rate, and ambulance diversion, as well as increased patient satisfaction. ACADEMIC EMERGENCY MEDICINE 2014; 21:266 273 2014 by the Society for Academic Emergency Medicine Internationally, emergency medical care systems are overburdened with patients backing up in the emergency department (ED) because they cannot get admitted to their inpatient beds in a timely fashion. 1 This predicament of overcrowding led the Institute of Medicine (IOM) to describe emergency medicine (EM) From the Department of Emergency Medicine, The Permanente Medical Group, Kaiser Permanente Medical Centers (PBP, DRV), Sacramento and Roseville, CA; and the Biostatistical Consulting Unit, Division of Research, Kaiser Permanente (MAC), Oakland, CA. Received June 16, 2013; revision received August 16, 2013; accepted September 12, 2013. Funded by a Kaiser Permanente Northern California Central Research Committee Community Benefit Grant, The Permanente Medical Group, Division of Research, Kaiser Permanente. The authors have no relevant financial information or potential conflicts of interest to disclose. Supervising Editor: Sandra M. Schneider, MD. Address for correspondence and reprints: Pankaj B. Patel, MD; e-mail: Pankaj.Patel@KP.org. ISSN 1069-6563 2014 by the Society for Academic Emergency Medicine 266 PII ISSN 1069-6563583 doi: 10.1111/acem.12327

ACADEMIC EMERGENCY MEDICINE March 2014, Vol. 21, No. 3 www.aemj.org 267 as in crisis, even at the breaking point. 1 Prolonged admit wait times for patients being held in the ED until the inpatient ward can accept them (a practice known as boarding ) is a significant cause of ED congestion and crowding. 2 11 The adverse effects of prolonged admit wait times and the concomitant ED crowding are profound and include measurable increases in patient morbidity and mortality, longer lengths of stay (LOS), more patients who leave without being seen (LWBS), and increased costs. 5,6,12 26 Prolonged admit wait time is a major cause for ambulance diversion, which directs patients away from their desired hospital destinations and delays their care. 1,19,27 29 Patient satisfaction is also adversely affected by ED crowding and admit wait time delays. 30,31 Because boarding admitted patients contributes significantly to ED crowding, the IOM has recommended an end to this practice. 1,32 Several studies have demonstrated the significant advantages that result from reducing admit wait times, which can relieve ED congestion by decreasing ED LOS, 13,27,33 ambulance diversion hours, 27,29,33 patients who LWBS, 29 and costs. 34 Although various solutions to reduce ED boarding have been identified, these proven strategies appear to be underutilized, as most hospitals report having implemented very few of them. 35,36 ED crowding can be reduced by expediting the transfer of admitted patients out of the ED, thereby reducing boarding times for patients held in the ED awaiting transfer to inpatient units. Our ED implemented a leadership-based admit wait time reduction program and then measured and analyzed the effect of this approach to expediting ED hospital admissions on admit wait times, boarding times, LOS, patient satisfaction, LWBS patients, and ambulance diversion hours. METHODS Study Design This was a retrospective, observational, before-andafter study to compare the effects of a leadership-based intervention on admit wait times and boarding time. The Kaiser Permanente Northern California Health Services Institutional Review Board reviewed this study and granted it an exemption from full review. Study Setting and Population We conducted this study between January 2006 and December 2011 at one urban community hospital within a large integrated health care delivery system serving approximately 3.3 million members at 21 hospitals and over 160 medical offices. The study hospital has 287 licensed beds with units for intensive care, telemetry, general medical surgical, neuroservices (includes neurosurgery), and oncology, but is not a designated trauma center. The hospital is affiliated with the University of California, Davis, School of Medicine with rotating residents from allergy/immunology, EM, family medicine, internal medicine, neurosurgery, obstetrics/gynecology, ophthalmology, orthopedics, pediatrics, plastic surgery, podiatry, radiology, surgery, and urology. The ED is staffed by one group of EM board-certified or board-eligible physicians and provides care to a broad spectrum of patients that include pediatric and obstetric patients (even though the hospital does not have inpatient pediatric or obstetric services). There were no significant changes to ED staffing during the study period. The average annual ED census during the study period was 76,169 patients. Study Protocol A process improvement plan was developed to reduce admit wait times, including all hours of the day and week (nights, weekends, and holidays). A team of ED and hospital leaders was convened to work toward admit wait time reduction. A computerized tracking system called HealthConnect (Epic Systems Corporation, Verona, WI) was used to monitor inpatient and ED bed status in real time to assess admit wait times for every ED patient who required admission to the hospital. Measurable steps, goals, and reports were identified and developed. Top leadership collaboratively and consistently tracked wait time metrics to assure progress toward the goal of admit wait time reduction (see Figure 1). No significant changes were made in ED work flow or emergency physician staffing during the 1. Patient enters ED LOS for admitted patient = from step #1 to step #7 2. Evaluation by ED physician 3. Evaluation by consultant/hospitalist 4. Decision to admit patient by consultant/hospitalist 5. Inpatient bed requested by ED staff Hospital target interval = 30 minutes from step #5 to step #6 6. Patient accepted by hospital and inpatient bed assigned Admission wait time = from step #5 to step #7 (goal = 60 minutes) 7. Patient leaves the ED for inpatient bed in hospital unit ED target interval = 30 minutes from step #6 to step #7 Figure 1. Flow diagram for ED process time intervals. LOS = length of stay.

268 Patel et al. ADMISSION WAIT TIME REDUCTION study period. Consulting physicians were responsible for determining which patients required admission to the hospital and alerted the ED staff to their decisions to admit by entering the order admit to hospital into the tracking system, which initiated the request for the appropriate inpatient bed. This electronic entry became the starting time for the admit wait time interval. Once the overall goal was established to admit ED patients within 60 minutes of the bed requests, the overall admit wait time was divided into two interval segments that were captured on the tracking system: 1) from the time an inpatient bed was requested to the time the hospital ward accepted the ED patient (this was the primary responsibility of hospital staff) and 2) from the time the ED patient was accepted by the inpatient ward to the time the ED patient left the ED (this was the primary responsibility of ED staff). Hospital and ED staff each sought to achieve their respective interval segments within 30 minutes. If hospital staff and ED staff each met their target goals, admission was achievable within the overall 60-minute goal (less than 30 minutes by hospital and less than 30 minutes by ED). The period from January 2006 through January 2008 was the preintervention period. In February 2008, the admission wait time reduction program was implemented. Interventions included the following: hospital and ED leadership meetings with nurse managers, charge nurses, admitting department, discharge planning, information technology, housekeeping and environmental services, physicians, and pharmacy; the systematic dissemination of tracked admit wait time data for everyone to review; and the real-time contact between leaders and their staff, to improve the flow of admitted patients from the ED to the inpatient wards. At regular meetings and via e-mail distribution, daily, weekly, and monthly tracking data were made available for everyone to review. Top leadership reviewed this information frequently and often made direct contact with their staff in real time if delays were observed in either of these two interval segments, allowing immediate resolution of issues that were causing the delays. The admit wait time reduction program required collaborative staff involvement from the ED, admitting department, hospital inpatient ward, discharge planning, housekeeping and environmental services (to get beds cleaned and ready for newly admitted patients), and information technology (to assure tracking system functioning). The ED had 36 rooms and nine urgent care rooms which were physically separate from the main ED, for a total of 45 rooms. In January 2010, the urgent care section was closed, resulting in a total ED bed capacity of 36 rooms, with all patients managed thereafter in the 36-room ED (including those who had previously presented to the ED and had been triaged to the urgent care section). The urgent care closure did not affect the processes for admission, as the admission rate for this group of patients was well below 1%. All of these patients who previously came through the ED had medical screening examinations performed by credentialed ED nurses and were then sent to the urgent care located on site, but outside the footprint of the ED. As the admit wait time process was streamlined, these patients were kept within the ED itself, incorporating the urgent care staff into the ED as well. The postintervention period was from February 2008 through December 2011. Outcome Measures Emergency department bed capacity, ED census, and overall admission rates were collected. The primary outcome measures were the percentage of ED patients admitted to inpatient beds within 60 minutes from the time the beds were requested and ED boarding time per admission. Explicit measures of ED throughput and patient satisfaction were collected, both before and after the implementation of the admit wait time reduction program. Summarized monthly outcome data included percentage of patients admitted within 60 minutes, boarding time per admission, LOS (for admitted patients, discharged patients, and all patients), overall boarding time, patient satisfaction scores, percentage of patients who LWBS, and ambulance diversion hours. The patient satisfaction survey used in this study was not specifically designed for this project and has been previously described as a proprietary survey for our organization. 37 Briefly, our medical group s regional Department of Access and Service Assessment sends out surveys to patients who have been seen in each of the 21 hospital EDs in our Northern California region. Questions on the survey cover a variety of parameters of ED care, including evaluation of the ED physician, the coordination of care during the ED visit, and courtesy and helpfulness of the staff. The patients are asked to rate each item using a five-point Likert scale: poor, fair, good, very good, and excellent. The reported score is the total percentage of patients who rank their overall ED care as very good or excellent. Annually, the regional department sent approximately 10,000 surveys to patients who had been treated in the study ED, with approximately 2,500 returned surveys from which patient satisfaction scores are reported for this study. Data Analysis Descriptive measures of the variables were calculated. We present continuous data as medians with interquartile ranges (IQRs). Variables were compared for significance pre- and post program implementation using the Wilcoxon-Mann-Whitney rank-sum test. Spearman correlations and significance were calculated to assess the bivariate influence each continuous confounder had on each outcome. A categorical variable indicating the decrease in ED bed capacity from 45 to 36 beds after January 2010 was used in the analysis. The bivariate effects of this categorical variable on each outcome were calculated using the Wilcoxon-Mann-Whitney rank-sum test. To determine if there were any trending, seasonal, or autoregressive effects that needed to be controlled for in the outcomes, we first chose to conduct an interrupted time series analysis. We used an autoregressive, integrated, moving average (ARIMA) model for each outcome. Ultimately, multivariable linear regression models were used to assess the effect of program implementation on the outcome measures when controlling for continuous and categorical confounders. Data were analyzed using SAS 9.3 for Windows (SAS Institute Inc., Cary, NC).

ACADEMIC EMERGENCY MEDICINE March 2014, Vol. 21, No. 3 www.aemj.org 269 RESULTS During the study period (2001 to 2011), average annual census was 76,169 with average annual admissions of 9,364 (12.3%). Annual mean data are presented in Table 1. Actual pre- and postimplementation data (median, IQR) at the program site on patients admitted within 60 minutes are shown in Figure 2. Boarding time per admission, LOS, patient satisfaction, LWBS patients, ambulance diversion hours, ED census, hospital admission rates, and ED bed capacity are noted in Table 2. We examined the correlation between the confounding variables and the outcomes to directly assess the effect on ED throughput that can be attributed to these factors. Spearman s correlation coefficients and corresponding p-values were calculated between the three confounding variables (ED census, hospital admission rates, and ED bed capacity) and each of the outcome variables (results not reported). We used an ARIMA model to assess for trends and autoregressive factors. When no autoregressive factors were identified (including seasonal trends), we continued the analysis using multivariable linear regression for parsimony. In our multivariable linear regression analysis (see Table 3), after controlling for the confounding variables listed above, there was an increase in patients being admitted within 60 minutes to the hospital of 16 percentage points (95% CI = 10 to 22; p < 0.0001), an average decrease in boarding time per admission of 46 minutes, and an average decrease in LOS for admitted patients of 79 minutes. There was also an average increase in patient satisfaction of 4.9 percentage points, a decrease in LWBS patients by 0.9 percentage points, and a decrease in ambulance diversion of 8.2 hours per month Staff from the urgent care were absorbed into the ED after the urgent care was closed. A review of physician and nonphysician staffing during the entire study period was performed and found that staffing matched census trends. Nursing staff changes closely reflected census changes, in line with state-required nurse staffing ratios. DISCUSSION A leadership-based program to reduce admit wait times was associated with a significant increase in the percentage of patients admitted to the hospital within 60 minutes and a significant decrease in boarding time per admission. This admit wait time reduction program was also associated with decreased LOS, reduced LWBS patients, reduced ambulance diversion hours, and improved patient satisfaction. Of note, ambulance diversion reduction efforts were ongoing prior to this study. 28,38 Regulatory agencies have delved into the issue of overcrowding and admitted patients who are boarded in EDs. The IOM called for an end to ED boarding through strong standards set by The Joint Commission. 1 Multipronged approaches to reduce boarding have been identified and used in various hospitals around the country. 4,23,35,36,39 43 It has been noted that failure by hospitals to address boarding in a voluntary fashion could result in penalties, public reporting Table 1 Annual Mean Data Ambulance Diversion (Hours) Patient Satisfaction (%) Left Without Being Seen (%) LOS Discharged Patients (hr:min) LOS All Patients (hr:min) LOS Admits (hr:min) Boarding Minutes/Admit Boarding Time (Hours) Admit* Within 60 Minutes (%) Admit Rate (%) ED Census Admissions Year 2006 74,164 10,130 13.7 33.5 15,627 93 8:35 4:57 3:57 1.7 67.6 116 2007 75,044 9,403 12.5 34.4 13,365 85 8:35 4:46 3:52 1.1 67.1 138 2008 78,818 9,934 12.6 36.4 14,539 88 8:26 4:48 3:55 1.1 69.7 107 2009 79,551 9,093 11.4 52.6 6,221 41 7:10 4:09 3:33 0.3 73.4 31 2010 73,907 9,070 12.3 59.7 4,893 32 6:40 3:21 2:53 0.5 73.4 13 2011 75,532 8,556 11.3 66.9 2,938 21 6:19 3:14 2:50 0.6 76.0 0 68 (54) 71.2 (3.3) 0.9 (0.5) 3:30 (0:28) 4:12 (0:41) 7:37 (0:56) 60 (29) 9,597 (5,047) 47.3 (13.2) 12.3 (0.8) 9,364 (536) 76,169 (2,208) Mean (SD) LOS = length of stay. *January April 2006 data not available

270 Patel et al. ADMISSION WAIT TIME REDUCTION Figure 2. Percent admitted within 60 minutes. Points graphed are percentages of patients admitted within 60 minutes for each month with program start date identified by arrow. Lines on figure represent least-squares regression for the pre- (January 2006 January 2008) and postintervention (February 2008 December 2011) data separately. imperatives, and increased regulations. 35,42 Although eventually vetoed by the state s governor, California state legislation to address ED crowding and boarding was introduced that would have required EDs to develop a crowding scale and implement protocols to address crowding when certain scores were reached. 44 While outside forces help support our efforts to reduce ED crowding, we implemented an internal process with active leadership involvement to address admit wait times. Multiple means have been employed to expedite the transfer of admitted ED patients to their inpatient beds. One successful approach was achieved by improving direct communications between emergency physicians and admitting hospitalists. 30 Some hospitals have given emergency physicians the authority to initiate the admission process to directly move ED patients to the inpatient setting, effectively reducing admit wait times. 27,39 An active hospitalist bed management program improved ED throughput for admitted patients by 98 minutes (from 458 minutes to 360 minutes) and reduced ambulance diversion (but with no effect upon patients who were discharged from the ED), resulting in improved collaboration with other physicians, nurses, and case managers. 40,45 Admit wait times for ICU patients were similarly reduced by 99 minutes (from 353 minutes to 254 minutes) when hospitalists were actively involved in bed management. 46 Although our study did not specifically address consultant wait times, communications between emergency physician and hospital staff using a hospital-wide computer tracking system had already been implemented across our hospital system with some measure of success. 47 However, this practice was in place prior to our interventions and alone was insufficient to reduce admit wait times to the levels we desired. Effective strategies to reduce admit wait times require involvement by all personnel within a hospital system 21,23 to systematically address admit wait times and ED boarding problems. 11,41,42 Senior management (effective ED leaders who get buy-in from their ED group and who work with hospital administration through a quality improvement group) is especially important in this effort. This was the design of our leadership-based program, and admit wait time reduction was eventually achieved in our study through collaboration between the hospital and ED, with active involvement and commitment by top leadership, using a hospital-wide computer tracking system to quantify and monitor admit wait times. Table 2 Pre- and Postintervention Outcomes Variable Preimplementation (25 Months, Jan. 2006 Jan. 2008), Median (IQR) Pre- and Postimplementation* Postimplementation (47 Months, Feb. 2008 Dec. 2011), Median (IQR) p-value Outcomes Patients admitted within 60 minutes (%) 35 (28 40) 58 (49 64) <0.001 Boarding time per admission (min) 82 (61 112) 26 (20 42) <0.001 LOS Admitted patients (hr:min) 8:47 (7:56 9:17) 6:49 (6:29 7:19) <0.001 Discharged patients (hr:min) 3:53 (3:49 4:01)) 3:03 (2:53 3:41) <0.001 All patients (hr:min) 4:46 (4:41 5:06) 3:31 (3:17 4:21) <0.001 Patient satisfaction (%) 66.9 (66.3 68.1) 73.6 (72.2 75.4) <0.001 Patients LWBS (%) 1.2 (0.9 1.6) 0.6 (0.1 0.9) <0.001 Monthly ambulance diversion (hours) 10 (3 15) 1 (0 3) <0.001 Confounders Monthly ED census 6,204 (6,051 6,407) 6,385 (6,107 6,640) NS Hospital admission rate (%) 12.8 (12.4 13.8) 11.9 (11.2 12.8) <0.001 ED bed capacity (exam rooms) 45 36 NS IQR = interquartile range; LOS = length of stay; LWBS = leave without being seen; NS = not significant. *Program implemented February, 2008. Patients admitted within 60 minutes data not available January 2006 April 2006. Patient satisfaction reported as percentage of patients who rate their care very good or excellent. ED bed capacity decreased January 2010 from 45 to 36 beds.

ACADEMIC EMERGENCY MEDICINE March 2014, Vol. 21, No. 3 www.aemj.org 271 Table 3 Multivariable Regression Results: Average Contribution of Program to Outcomes* Changes Between Preintervention (Jan. 2006 Jan. 2008) and Postintervention (Feb. 2008 Dec. 2011) Parameter Estimate Variable Change 95% CI p value Admission within 60 minutes,% 16 10 to 22 <0.0001 Boarding time per admission, minutes 46 63 to 28 <0.0001 LOS, minutes Admitted patients 79 104 to 55 <0.0001 Discharged patients 17 23 to 12 <0.0001 All patients 34 43 to 25 <0.0001 Patient satisfaction,% 4.9 3.8 to 6.0 <0.0001 LWBS,% 0.9 1.2 to 0.6 <0.0001 Monthly ambulance diversion, hours 8.2 11.8 to 4.6 <0.0001 LOS = length of stay; LWBS = leave without being seen. *Controlling for ED census, hospital admission rates, and ED bed capacity. An organization-wide program in nine EDs in England uncovered findings similar to ours. The study highlighted the need to 1) emphasize the responsibility of the entire organization, not just the ED; 2) focus on improving patient care, avoiding premature movement of patients at risk; and 3) identify all stakeholders to achieve the target for optimal throughput. 48 Organizational efficiency and effectiveness improvement resulted from the collaboration and shared ownership of the process. Similarly, the University Health System ED in San Antonio, Texas, worked with its inpatient unit and housekeeping staff to reduce bed turnaround time from 160 minutes to less than 30 minutes, resulting in an 8.5% decrease in overall length of ED throughput time. 41 Similar to our findings, involvement and active support by top management was critical to reduce ED congestion and improve hospital patient flow. 35,41,48 One successful method for reducing admit wait times is to take admitted ED patients who would otherwise be boarded in ED hallways and move them directly to the hallways of their designated inpatient floors while they await open beds. 49 This practice has been implemented in some areas of the United States and was shown to be safe. 3 In fact, surveys have reported that patients prefer to wait in the hallways of the inpatient ward rather than in the hallways of the ED, 7,50,51 and it is estimated that this idea has spread to hundreds of hospitals nationwide. 49 Once patients have been admitted to inpatient hallways, inpatient ward staff have been able to more promptly identify inpatient beds for these admitted patients than if they had remained in the ED. 10 Despite the success of this practice elsewhere, moving boarded ED patients to inpatient hallways is prohibited by regulatory issues in California. Despite various efforts to evaluate its potential for success locally, we were unable to implement this option. LIMITATIONS The high-level summarized data used are likely to be influenced by external factors not included in the analysis, such as differences in the acuity of the populations served, as well as monthly variations in ED volume, as seen during the winter flu seasons. We mitigated the facility-specific variations by controlling for a number of measurable factors, including ED census, hospital admission rates, and bed capacity. When we performed a time series analysis, no autoregressive patterns were uncovered. This was an uncontrolled before-and-after study. Therefore, the observed changes could be due to the intervention or due to other secular trends that affected this particular ED, limiting the ability to invoke causality. CONCLUSIONS A leadership-based admit wait time reduction program was associated with an increase in the percentage of patients admitted to the hospital within 60 minutes and a reduction in ED boarding times. Following the implementation of this program, the reduction in physical bed capacity that resulted from the closure of the urgent care section of the hospital was manageable without significant repercussions due to an increase in effective ED bed capacity. The ED also achieved additional benefits that included decreased length of stay, reduced the number of patients who left without being seen, reduced ambulance diversion hours, and improved patient satisfaction. The authors thank the Kaiser Permanente Northern California Community Benefit Program for their financial support of this study. We appreciate Mary Anne Armstrong, MA, Director of the Biostatistical Consulting Unit, Kaiser Permanente Northern California Division of Research, for her review of our manuscript. We gratefully acknowledge members of the admit wait time reduction team from our hospital and ED, as well as our ED and hospital nurses for their tireless efforts to implement this program. Program implementation would not have been possible without active and enthusiastic involvement of Beverly Werntz, Chief Operating Officer, who worked closely with Kathy Miles, RN, ED Director. We also acknowledge the leadership role played by Dr. Jack Rozance, Physician in Chief. Finally, we appreciate the support of our emergency department leadership group. References 1. Institute of Medicine Committee on the Future of Emergency Care in the United States Health System. Hospital-based Emergency Care: At the Breaking

272 Patel et al. ADMISSION WAIT TIME REDUCTION Point. Washington, DC: National Academies Press, 2006. 2. Schneider S. A letter from ACEP president Sandra Schneider. Emerg Phys Monthly 2011;18:3. 3. Viccellio A, Santora C, Singer AJ, Thode HC Jr, Henry MC. The association between transfer of emergency department boarders to inpatient hallways and mortality: a 4-year experience. Ann Emerg Med 2009;54:487 91. 4. Moskop JC, Sklar DP, Geiderman JM, Schears RM, Bookman KJ. Emergency department crowding, part 1 concept, causes, and moral consequences. Ann Emerg Med 2009;53:605 11. 5. Stolte E, Iwanow R, Hall C. Capacity-related interfacility patient transports: patients affected, wait times involved and associated morbidity. CJEM 2006; 8:262 8. 6. Clark K, Normile LB. Influence of time-to-interventions for emergency department critical care patients on hospital mortality. J Emerg Nurs 2007;33:6 13. 7. Garson C, Hollander JE, Rhodes KV, Shofer FS, Baxt WG, Pines JM. Emergency department patient preferences for boarding locations when hospitals are at full capacity. Ann Emerg Med 2008;51:9 12. 8. Hoot NR, Aronsky D. Systematic review of emergency department crowding: causes, effects, and solutions. Ann Emerg Med 2008;52:126 36. 9. Olshaker JS, Rathlev NK. Emergency department overcrowding and ambulance diversion: the impact and potential solutions of extended boarding of admitted patients in the emergency department. J Emerg Med 2006;30:351 6. 10. Derlet RW, Richards JR. Ten solutions for emergency department crowding. West J Emerg Med 2008;9:24 7. 11. Millard WB. Stand by to repel boarders. Ann Emerg Med 2011;57:A15 19. 12. Sprivulis PC, Da Silva JA, Jacobs IG, Frazer AR, Jelinek GA. The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments. Med J Aust 2006;184:208 12. 13. Lucas R, Farley H, Twanmoh J, et al. Emergency department patient flow: the influence of hospital census variables on emergency department length of stay. Acad Emerg Med 2009;16:597 602. 14. Gilligan P, Winder S, Singh I, Gupta V, Kelly PO, Hegarty D. The Boarders in the Emergency Department (BED) study. Emerg Med J 2008;25:265 9. 15. Schull MJ, Vermeulen M, Slaughter G, Morrison L, Daly P. Emergency department crowding and thrombolysis delays in acute myocardial infarction. Ann Emerg Med 2004;44:577 85. 16. Phua J, Ngerng WJ, Lim TK. The impact of a delay in intensive care unit admission for communityacquired pneumonia. Eur Respir J 2010;36:826 33. 17. McCarthy ML, Zeger SL, Ding R, et al. Crowding delays treatment and lengthens emergency department length of stay, even among high-acuity patients. Ann Emerg Med 2009;54:492 503. 18. Plunkett PK, Byrne DG, Breslin T, Bennett K, Silke B. Increasing wait times predict increasing mortality for emergency medical admissions. Eur J Emerg Med 2011;18:192 6. 19. Falvo T, Grove L, Stachura R, et al. The opportunity loss of boarding admitted patients in the emergency department. Acad Emerg Med 2007;14:332 7. 20. Huang Q, Thind A, Dreyer JF, Zaric GS. The impact of delays to admission from the emergency department on inpatient outcomes. BMC Emerg Med 2010;10:16. 21. Pines JM, Batt RJ, Hilton JA, Terwiesch C. The financial consequences of lost demand and reducing boarding in hospital emergency departments. Ann Emerg Med 2011;58:331 40. 22. Bernstein SL, Aronsky D, Duseja R, et al. Society for Academic Emergency Medicine, Emergency Department Crowding Task Force. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med 2009;16:1 10. 23. Verdile VP. Sutton s Law need not apply. Ann Emerg Med 2011;58:341 2. 24. ACEP Board of Directors. Policy statement: definition of boarded patient. Ann Emerg Med 2011;57:548. 25. Sills MR, Fairclough D, Ranade D, Kahn MG. Emergency department crowding is associated with decreased quality of care for children with acute asthma. Ann Emerg Med 2011;57:191 200. 26. Singer AJ, Thode HC Jr, Viccellio P, Pines JM. The association between length of emergency department boarding and mortality. Acad Emerg Med 2011;18:1324 9. 27. Quinn JV, Mahadevan SV, Eggers G, Ouyang H, Norris R. Effects of implementing a rapid admission policy in the ED. Am J Emerg Med 2007;25:559 63. 28. Patel PB, Derlet RW, Vinson DR, Williams M, Wills J. Ambulance diversion reduction: the Sacramento solution. Am J Emerg Med 2006;24:206 13. 29. Kelen GD, Scheulen JJ, Hill PM. Effect of an emergency department (ED) managed acute care unit on ED overcrowding and emergency medical services diversion. Acad Emerg Med 2001;8:1095 100. 30. Howell EE, Bessman ES, Rubin HR. Hospitalists and an innovative emergency department admission process. J Gen Intern Med 2004;19:266 8. 31. Pines JM, Iyer S, Disbot M, Hollander JE, Shofer FS, Datner EM. The effect of emergency department crowding on patient satisfaction for admitted patients. Acad Emerg Med 2008;15:825 31. 32. Asplin BR, Magid DJ. If you want to fix crowding, start by fixing your hospital. Ann Emerg Med 2007;49:273 4. 33. Fatovich DM, Nagree Y, Sprivulis P. Access block causes emergency department overcrowding and ambulance diversion in Perth. Western Australia. Emerg Med J 2005;22:351 4. 34. Moloney ED, Smith D, Bennett K, O riordan D, Silke B. Impact of an acute medical admission unit on length of hospital stay, and emergency department wait times. QJM 2005;98:283 9. 35. Rabin E, Kocher K, McClelland M, et al. Solutions to emergency department boarding and crowding are underused and may need to be regulated. Health Aff 2012;31:1757 66.

ACADEMIC EMERGENCY MEDICINE March 2014, Vol. 21, No. 3 www.aemj.org 273 36. Sullivan L. Hospitals failing to address patient boarding. ACEP News 2012;31:11. 37. Patel PB, Vinson DR. Team assignment system: expediting emergency department care. Ann Emerg Med 2005;46:499 506. 38. Patel PB, Vinson DR. Ambulance diversion reduction and elimination: the 3-2-1 plan. J Emerg Med 2012;43:e363 71. 39. [No authors listed]. Study offers solutions for bottlenecks: treat and move patients in record time. ED Manag 2000;12:25 9. 40. Howell E, Bessman E, Kravet S, Kolodner K, Marshall R, Wright S. Active bed management by hospitalists and emergency department throughput. Ann Intern Med 2008;149:804 10. 41. McClelland MS, Lazar D, Sears V, Wilson M, Siegel B, Pines JM. The past, present, and future of urgent matters: lessons learned from a decade of emergency department flow improvement. Acad Emerg Med 2011;18:1392 9. 42. Ault A. Many ways to be waylaid between ED and inpatient bed. ACEP News 2012;31(1):12. 43. Johnson G. How one hospital curbs boarding. ACEP News 2012;31:13. 44. California Senate Bill SB 366. Emergency Room Crowding. Available at: http://www.leginfo.ca.gov/ pub/11-12/bill/sen/sb_0301-0350/sb_336_bill_20110516_ amended_sen_v97.html. Accessed Dec 1, 2013. 45. [No authors listed]. ED/hospitalist plan improves throughput. ED Manag 2009;21:70 1. 46. Howell E, Bessman E, Marshall R, Wright S. Hospitalist bed management effecting throughput from the emergency department to the intensive care unit. J Crit Care 2010;25:184 9. 47. [No author]. Milestones on the journey to worldclass hospitals. TPMG Forum 2012;24:1 5. 48. Weber EJ, Mason S, Carter A, Hew RL. Emptying the corridors of shame: organizational lessons from England s 4-hour emergency throughput target. Ann Emerg Med 2011;57:79 88. 49. Greene J. Emergency department flow and the boarded patient: how to get admitted patients upstairs. Ann Emerg Med 2007;49:68 70. 50. Bartlett S, Fatovich DM. Emergency department patient preferences for waiting for a bed. Emerg Med Australas 2009;21:25 30. 51. Walsh P, Cortez V, Bhakta H. Patients would prefer ward to emergency department boarding while awaiting an inpatient bed. J Emerg Med 2008; 34:221 6.